1. Glucose Monitoring Is it Worth It?
Self Monitoring of Blood Glucose & Continuous Glucose Monitoring
Joe Largay, PAC, CDE
Clinical Instructor Department Of Medicine University Of North Carolina

2. Learning Objectives:
Explain how to use glucose monitoring to self empower your patients with diabetes to improve their glycemic control
Compare and contrast Self Monitoring of Plasma Glucose (SMPG) and Continuous Glucose Monitoring (CGM)
List the benefits of Self Monitoring of Plasma Glucose (SMPG)
Describe how to use SMPG to identify glycemic patterns

3. Major Barriers to Achieving Glycemic Goals
Behavioral change
Lack of awareness of glycemic levels
Fear of hypoglycemia
Hirsch IB, et al. Diabetes Technol Ther. 2008;10(4):

4. Global Attitudes of Patients and Physicians in Insulin Therapy (GAPP™)
Fear of Hypoglycemia
67% of patients
74% providers
67 % feel that diabetes has controlled their life since starting insulin
1 in 3 patients skip insulin doses at least 3 times per month
Too busy
Change in normal routines
Forget to take
The Global Attitudes of Patients and Physicians in Insulin Therapy (GAPP™) survey was conducted in eight countries with the objective to learn what physicians and patients perceive to be the biggest functional and emotional unfulfilled needs and challenges in the management of diabetes today, specifically relating to insulin treatment. Independent research analysts conducted a 20-minute quantitative survey among 2,780 respondents in the US, UK, Germany, Spain, France, China, Japan and Turkey. The respondents were made up of 1,250 physicians (n=650 PCPs; n=600 specialists) and 1,530 insulin-using diabetes patients (n=180 type 1, n=1,350 type 2).
Change in normal routines, being too busy or simply forgetting to take the insulin are the main reasons cited by both patients and physicians for patients missing insulin doses.
Another key factor that may contribute to poor glycemic control is fear of hypoglycemia. Sixty-seven percent of patients taking insulin are concerned about experiencing a hypoglycemic event in the future and physicians share patients' concerns with 74 percent stating that they would treat closer to recommended targets if it weren't for fear of major hypoglycemic events.
People with diabetes are looking for less invasive insulin options
The survey also revealed that nine in 10 patients wish there was an insulin that could be dosed less than once a day and effectively manage blood sugar and 67 percent of them feel that diabetes has controlled their life since starting insulin. At the same time, the survey reveals a third of physicians are dissatisfied with current regimens' ability to fit into patients dynamic lifestyles.

5. Hypoglycemia and CV Disease
ACCORD: Symptomatic, severe hypoglycemia was associated with an increased risk of death whether participants were in the intensive arm or the standard arm1
Patients with hypoglycemic events had 79% higher regression-adjusted odds of acute cardiovascular events, than patients without (odds ratio [OR] 1.79; 95% CI 1.69–1.89)
Results 10 194 of the 10 251 participants enrolled in the ACCORD study who had at least one assessment for hypoglycaemia during regular follow-up for vital status were included in this analysis. Unadjusted annual mortality among patients in the intensive glucose control arm was 2.8% in those who had one or more episodes of hypoglycaemia requiring any assistance compared with 1.2% for those with no episodes (53 deaths per 1924 person years and 201 deaths per 16 315 person years, respectively; adjusted hazard ratio (HR) 1.41, 95% CI 1.03 to 1.93). A similar pattern was seen among participants in the standard glucose control arm (3.7% (21 deaths per 564 person years) v 1.0% (176 deaths per 17 297 person years); adjusted HR 2.30, 95% CI 1.46 to 3.65). On the other hand, among participants with at least one hypoglycaemic episode requiring any assistance, a non-significantly lower risk of death was seen in those in the intensive arm compared with those in the standard arm (adjusted HR 0.74, 95% 0.46 to 1.23). A significantly lower risk was observed in the intensive arm compared with the standard arm in participants who had experienced at least one hypoglycaemic episode requiring medical assistance (adjusted HR 0.55, 95% CI 0.31 to 0.99). Of the 451 deaths that occurred in ACCORD up to the time when the intensive treatment arm was closed, one death was adjudicated as definitely related to hypoglycaemia.
Conclusion Symptomatic, severe hypoglycaemia was associated with an increased risk of death within each study arm. However, among participants who experienced at least one episode of hypoglycaemia, the risk of death was lower in such participants in the intensive arm than in the standard arm. Symptomatic, severe hypoglycaemia does not appear to account for the difference in mortality between the two study arms up to the time when the ACCORD intensive glycaemia arm was discontinued.
OBJECTIVE—This retrospective study examined the association between ICD-9-CM–coded
outpatient hypoglycemic events (HEs) and acute cardiovascular events (ACVEs), i.e., acutemyocardial
infarction, coronary artery bypass grafting, revascularization, percutaneous coronary intervention,
and incident unstable angina, in patients with type 2 diabetes.
RESEARCH DESIGN AND METHODS—Data were derived from healthcare claims for
individuals with employer-sponsored primary or Medicare supplemental insurance. A baseline
period (30 September 2006 to 30 September 2007) was used to identify eligible patients
and collect information on their clinical and demographic characteristics. An evaluation
period (1 October 2007 to 30 September 2008) was used to identify HEs and ACVEs. Patients
aged $18 years with type 2 diabetes were selected for analysis by a modified Healthcare
Effectiveness Data and Information Set algorithm. Data were analyzed with multiple logistic
regression and backward stepwise selection (maximum P = 0.01) with adjustment for important
confounding variables, including age, sex, geography, insurance type, comorbidity scores,
cardiovascular risk factors, diabetes complications, total baseline medical expenditures, and
prior ACVEs.
RESULTS—Of the 860,845 patients in the analysis set, 27,065 (3.1%) had ICD-9-CM–coded
HEs during the evaluation period. The main model retained 17 significant independent variables.
Patients with HEs had 79% higher regression-adjusted odds (HE odds ratio [OR] 1.79; 95%
CI 1.69–1.89) of ACVEs than patients without HEs; results in patients aged $65 years were
similar to those for the entire population (HE OR 1.78, 95% CI 1.65–1.92).
CONCLUSIONS—ICD-9-CM–coded HEs were independently associated with an increased
risk of ACVEs. Further studies of the relationship between hypoglycemia and the risk of ACVEs
are warranted.
Diabetes Care 34:1164–1170, 2011
ACCORD:
Definition of hypoglycaemia
Participants were asked at every visit if they had experienced episodes of low blood sugar. Circumstances surrounding episodes of symptomatic, severe hypoglycaemia were investigated further by the research staff and information on precipitating events, symptoms, and consequences were recorded. All symptomatic, severe hypoglycaemic events were reported to the coordinating centre, and those events requiring medical assistance were reported as serious adverse events.
A full description of the review and adjustment of therapeutic goals in response to severe hypoglycaemia has been previously reported.11 Briefly, all hypoglycaemic events reported as serious adverse events were reviewed internally by an expert in diabetes care and externally by an independent advisory board. After a participant had experienced three hypoglycaemic events requiring medical assistance, their haemoglobin A1C goal was altered. Review of hypoglycaemic events and procedures for goal alteration were the same regardless of study arm.
Three separate definitions of hypoglycaemia were used to evaluate possible associations between hypoglycaemia and mortality. Each of these approaches is described below.
Symptomatic, severe hypoglycaemic event requiring medical assistance (HMA)
At each visit, participants were asked if they had experienced an episode of severe hypoglycaemia in which they had received care at a hospital, at an emergency room, or from medical personnel. Symptomatic, severe hypoglycaemia was defined as either a blood glucose concentration of less than 2.8 mmol/l (50 mg/dl) or symptoms that promptly resolved with oral carbohydrate, intravenous glucose, or subcutaneous or intramuscular glucagon.
Symptomatic, severe hypoglycaemic event requiring any assistance (HA)
Hypoglycaemia needing any assistance was defined as an episode of symptomatic, severe hypoglycaemia in which the participant reported receiving either medical care or assistance from another individual and had either a documented blood glucose concentration of less than 2.8 mmol/l (50 mg/dl) or recovery with carbohydrate treatment.
Hypoglycaemia based on a finger stick blood glucose measurement of less than 3.9 mmol/l in self report log
At each visit, the number of blood sugar values below 3.9 mmol/l (70 mg/dl) in the previous seven days was determined from the finger stick glucose record maintained by the participant or from information downloaded from the participant’s glucose monitoring meter.
In this study, there are 19 fewer hypoglycaemic events at the time the intensive glycaemia control intervention was stopped than in previous reports6 because this paper’s analyses only include hypoglycaemic events that occurred before an official four month assessment for vital status within each glycaemia arm.
1. BMJ 2010; 340:b4909
2.Diabetes Care 34:1164–1170, 2011

6. ACCORD-Determinants of Hypoglycemia
Rates of severe hypoglycemia were more common in the intensive as compared to the standard group (3.14% vs. 1.03%)
Highest rates seen in :
African-Americans
Older participants
On insulin therapy at trial entry
Women
Lower levels of educational achievement
Higher baseline A1c
Greater lowering of A1C during the first 4 months was associated with lower risk of severe hypoglycemia
Miller, M. et al, 8 January 2010, doi: /bmj.b5444
Results The annual incidence of hypoglycaemia was 3.14% in the intensive treatment group and 1.03% in the standard glycaemia group. We found significantly increased risks for hypoglycaemia among women (P=0.0300), African-Americans (P< compared with non-Hispanic whites), those with less than a high school education (P< compared with college graduates), aged participants (P< per 1 year increase), and those who used insulin at trial entry (P<0.0001). For every 1% unit decline in the haemoglobin A1C concentration from baseline to 4 month visit, there was a 28% (95% CI 19% to 37%) and 14% (4% to 23%) reduced risk of hypoglycaemia requiring medical assistance in the standard and intensive groups, respectively. In both treatment groups, the risk of hypoglycaemia requiring medical assistance increased with each 1% unit increment in the average updated haemoglobin A1C concentration (standard arm: hazard ratio 1.76, 95% CI 1.50 to 2.06; intensive arm: hazard ratio 1.15, 95% CI 1.02 to 1.21).
Conclusions A greater drop in haemoglobin A1C concentration from baseline to the 4 month visit was not associated with an increased risk for hypoglycaemia. Patients with poorer glycaemic control had a greater risk of hypoglycaemia, irrespective of treatment group. Identification of baseline subgroups with increased risk for severe hypoglycaemia can provide guidance to clinicians attempting to modify patient therapy on the basis of individual risk.
Within both intensive and standard glycemia groups, participants who had higher baseline A1C’s had greater risk of HMA than those with lower values. After controlling for baseline covariates, this effect was only seen within the standard group. Contrary to some suggestions, greater lowering of A1C during the first 4 months was associated with lower risk of severe hypoglycemia.

7. Type 2 DM and CV Disease Risk Reduction: Lessons From ADVANCE, ACCORD, VADT, & UKPDS
Achieve better blood glucose levels to prevent microvascular complications in patients earlier in the course of their diabetes
Individualize glucose goals for patients with advanced CVD
In older, high-risk patients with CVD, maintain A1C close to 7%, not necessarily <7%
Use more intense blood glucose control to modestly reduce CVD risk in those with early DM w/o advanced atherosclerotic disease. In these individuals, an A1C target of 6.5% or less may be appropriate
Avoid hypoglycemia
Focus also on lipid lowering, BP reduction, antiplatelet therapy, smoking cessation, and antihyperglycemic agents
Type 2 DM and CV Disease Risk Reduction: Lessons From ADVANCE, ACCORD, VADT, & UKPDS
The ADVANCE, ACCORD, VADT, and UKPDS studies have provided some guidance for treating patients with type 2 diabetes, including these:
We should work to achieve better blood glucose levels to prevent microvascular complications in patients earlier in the course of their diabetes
Glucose goals should be individualized for patients with advanced CVD
-In older, high-risk patients, maintain A1C close to 7%, not necessarily <7%
More intense blood glucose control can be used to modestly reduce CVD risk in those with early DM without advanced atherosclerotic disease. In these individuals, an A1C target of 6.5% or less may be appropriate
We should help patients avoid hypoglycemia
Additional focus on lipid-lowering, BP reduction, anti-platelet therapy, smoking cessation, and antihyperglycemic agents is prudent
Most of all, T2DM should be treated early

8. Individualizing Treatment Goals
Goals should be individualized based on:
● duration of diabetes
● age/life expectancy
● comorbid conditions
● known CVD or advanced microvascular
complications
● hypoglycemia unawareness
● individual patient considerations
● More or less stringent glycemic goals may be
appropriate for individual patients.
● Postprandial glucose may be targeted if A1C goals are
not met despite reaching preprandial glucose goals.

9. Measures of Success
A1C
provides the “big picture” - the average glycemia levels during previous 90 days (but is more heavily weighted by the most recent values) and correlates with end-organ impact
SMBG (Self Monitoring of Blood Glucose)
patterns provide day-to-day data used to select and manage glucose control programs and ultimately optimize A1C:
Provide a measure of the specific pharmacologic impact of oral treatment medications
Allow design and implementation of physiologic insulin-replacement programs

10. 2011 Glycemic Goals of Therapy
Premeal capillary plasma glucose (mg/dl)
Peak postprandial capillary plasma glucose
HbA1c
ADA
70-130
<180*
ACE
<110
<140
< 7% < 6.5%
A reasonable
recommendation for postprandial
testing and targets is that for individuals
who have premeal glucose values within
target but have A1C values above target,
monitoring postprandial plasma glucose
(PPG) 1–2 h after the start of the meal and
treatment aimed at reducing PPG values
to 180 mg/dl may help lower A1C.
*A reasonable recommendation for postprandial testing and targets is that for individuals who have premeal glucose values within target but have A1C values above target, monitoring postprandial plasma glucose (PPG) 1–2 h after the start of the meal and treatment aimed at reducing PPG values to 180 mg/dl may help lower A1C.
ADA. Diabetes Care 2011:34(S1):S11-S61
Rodbard HW et al, Endo Pract. 2007; 13:1-68

11. SMBG – Part of Self Management Skills

12. Is SMBG Beneficial?
Polonsky WH, Fisher L, Schikman CH, et al. Structured self-monitoring of blood glucose significantly reduces A1C levels in poorly controlled, noninsulin-treated type 2 diabetes. Diabetes Care. 2011;34(2):
Polonsky WH, Fisher L, Schikman CH, et al. Structured self-monitoring of blood glucose significantly reduces A1C levels in poorly controlled, noninsulin-treated type 2 diabetes. Diabetes Care. 2011;34(2):

13. Is SMBG Beneficial?
Polonsky WH, Fisher L, Schikman CH, et al. Structured self-monitoring of blood glucose significantly reduces A1C levels in poorly controlled, noninsulin-treated type 2 diabetes. Diabetes Care. 2011;34(2):
Polonsky WH, Fisher L, Schikman CH, et al. Structured self-monitoring of blood glucose significantly reduces A1C levels in poorly controlled, noninsulin-treated type 2 diabetes. Diabetes Care. 2011;34(2):

14. Limitations and Potential Errors with SMBG
Sample contamination (dirty hands)
Insufficient blood on strip
Incorrect insertion of strip into meter
Outdated strips
Failure to perform quality control
Incorrect strip code entered in meter
Incorrect units of measure (mg/dl vs. mmol)

15. Limitations and Potential Errors with SMBG
Altitude (6.5-15% variability)
Temperature
Hematocrit (inverse relationship)

16. Self Monitoring Blood Glucose Log
Fasting
Lunch
Before Soccer Practice
Supper
Bed
2 am 99
187
182 67
105 84
211
192
123 56
202
143
259 75
236
158
107
181
178 94
127 64
This shows a pattern of hypoglycemia after soccer practice (EIH) and again overnight (PEH)

17. Self Monitoring Blood Glucose Log Paired Readings
Fasting
After
Breakfast
Before
Lunch
Dinner
101
132 87
267 97
158
286
189
131
304 85
222
This shows a pattern of hyperglycemia after meals

18. SMBG Log T2DM on Prednisone
Time of Day
Before start of Prednisone
After start of Prednisone
Before Breakfast
77-119
Before Lunch
95-136
Before Supper
Bedtime
“c/o increased urination and feeling tired late in the day since starting steroids”

19. The Role of Continuous Glucose Monitoring (CGM) in the Management of Diabetes
The Devil is in the Details
Joe Largay, PAC, CDE
Clinical Instructor
Department of Medicine
Division of Endocrinology
University of North Carolina

20. With SMBG, Diabetes Patients Are Essentially Blindfolded
Complex Carbs
Simple Carbs
Fatty Meal
French Meal
Slow
Very
Slow
Fast
constipation
insomnia
exposure to cold
menstruation
illness
medication
emotion
stress
time change
caffeine
smoking
Still there the next day
All these variables play a role in daily glucose control and … every day is a different day.
Blood Glucose Levels
Gastroparesis
See French Meal
Rapid
Variable
Sustained
Exercise
Digestion
Brain Function
2% of body mass, 25% of glucose consumption

21. Real-Time Continuous Glucose Monitoring (CGM) Systems
Abbott FreeStyle Navigator®
DexCom™ SEVEN® PLUS
Medtronic MiniMed Paradigm® REAL-Time Revel™

22. SMBG Does Not Give Patients the Whole Picture
350
280
210
Glucose (mg/dL)
140 70 2 4 6 8 10 12 14 16 18 20 22 24
Time (Hours)
Based on simulated data.

23. CGM Systems1-4
Currently most CGM systems use an electrochemical process for glucose sensing
Three major CGM devices have been approved by the FDA
All available CGM devices read glucose values in the Interstial Fluid Space (ISF)
1. FreeStyle Navigator® Product Fact Sheet. Abbott Diabetes Care; 2008.
2. FreeStyle Navigator® Product Brochure. Abbott Diabetes Care; 2007.
3. Paradigm® REAL-Time User Guide. Medtronic MiniMed; 2007.
4. SEVEN® User’s Guide. DexCom; 2009.

24. What Is Calibration?
Sensor calibration is the pairing of the fingerstick (FS) value to the sensor value from the interstitial fluid (ISF) space
FS measures plasma-calibrated blood
Sensor reads electrical current produced by glucose oxidase reaction
Calibration confirms sensor accuracy during various points by “teaching” the sensor the glucose value that corresponds with the electrical current signal
Calibration is how the device learns what the signals from the sensor mean
Velho G, et al. Biomed Biochim Acta. 1989;48(11-12):

25. Comparison Matrix – Sensor
DexCom™
SEVEN® PLUS1
Medtronic Paradigm®
REAL-Time2
Abbott
FreeStyle Navigator®3
Sensor length
13 mm
14 mm
5 mm
Sensor introducer needle4
26 gauge
23 gauge
21 gauge
Sensor wear
Up to 7 days
Up to 3 days
Up to 5 days
Sensor start-up
2 hours
10 hours
Sensor sites
Abdomen
Abdomen, arm
Sensor packaging
4 packs
4 and 10 packs
6 pack
Glucose range
Calibration range
mg/dL
mg/dL
mg/dL
Insertion angle
45°
90°
1. SEVEN® User’s Guide. DexCom; 2009.
2. Paradigm® REAL-Time User Guide. Medtronic MiniMed; 2007.
3. FreeStyle Navigator® Users Guide. Abbott Diabetes Care; 2008.
4. Diabetes Health. 2008;Dec 08/Jan 09: health.com/read/08/12/29.html. Accessed January 19, 2009.

26. Product Price Comparisons 2011
DexCom™ SEVEN® PLUS
Medtronic Paradigm®
REAL-Time
Abbott
FreeStyle Navigator®
Starter kit list price
$1158
$1200
$1250 ??
Sensor cost/day
$17
$12
$15 ??

27. CGM Supports Patients in Proactive vs Reactive Self-Management
Helps to warn of impending hypoglycemia or hyperglycemia
Alerts/alarms help patient “stay between the lines”
Helps detect nocturnal events
Helps provide immediate feedback re: how changes in diet, exercise, stress, and insulin affect glucose levels
May help avoid overreaction and/or overtreatment of high or low glucose values by alerting to impending highs and lows
Supports pattern management
Tracking/trending provide series of multiple sequential glucose readings over time, can aid in diabetes self-management decisions

28. CGM Can Uncover Glucose Patterns That May Be the Cause of a High A1c
400
0.9h
7.6h
5.6h
2.9h
1.3h
300
4.3h
1.0h
0.5h
Glucose (mg/dl)
This patient seldom recovers from breakfast until the end of the day
200
100
Day Day Day Day Day 72
1440
2880
4320
5760
7200
Max.
Sensor
Reading
364
362
368
350
367
Undetected High Excursions With SMBG
53-year-old male, multiple injector; 240 lbs.; 10 yrs. diabetes; HbA1c 7.3
Data on file, DexCom. Study Number G ; RPT 2168.

29. CGM Professional Purchased and used in clinics Reimbursable
Clinicians can download data and review with patient

30. CGM Can Help Clinicians Help Patients
Provides insight into trending information/pattern management
Basal testing
Insulin on-board testing
Insulin-to-carbohydrate and correction dose testing
Insulin on-board timing
Identifies insulin action (insulin dose effect) and potential need for additional medication to control postprandial glucose
Provides information about timing of food digestion and timing of insulin administration based on food absorption
Provides continuous data for overnight basal testing and assessment of any nocturnal hypoglycemia

31. CGM Indications
Indicated for ages > 18 for use in addition to SMBG for the purpose of improving glycemic control
Supported by ADA and AACE Guidelines for glucose monitoring
To identify and aid in management of glycemic patterns not recognized with typical SMBG
To prevent glycemic excursions:
hypoglycemia
hyperglycemia

32. CGM is NOT Technology that can be used to dose insulin
All dosing decisions should be based on the SMBG
Replacement for glucose meter (SMBG)
Device to put on and “forget” about
Studies have shown a correlation between the number of times you look at the receiver and greater reduction in A1c1
System that replaces/is a substitute for already existing diabetes management tools
Bailey TS, et al. Diabetes Technol Ther. 2007;9( 3):

33. Continuous Glucose Monitoring and Intensive Treatment of Type 1 Diabetes (The Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group*)
In age group > 25 years old a decrease in A1c without increase in severe hypoglycemia
This was not seen in younger age groups 8-14 or 15-24
Success in lowering A1c correlates with individuals’ ongoing use of CGM
Patients who used CGM 6 days/week experienced a minimum of 0.5% reduction in A1c2
Greatest predicator of A1c lowering in the JDRF trial for all ages was frequency of sensor use
Success in lowering A1c correlates with individuals’ ongoing use of CGM
Patients who used CGM 6 days/week experienced a minimum of 0.5% reduction in A1c2
Greatest predicator of A1c lowering in the JDRF trial for all ages was frequency of sensor use
NEJ M 2008;359

34. CGM: Clinical Indications
Glycemic variability
Hypoglycemia
Hypoglycemia unawareness
Gastroparesis
Preconception
Behavior modification
Insulin-requiring DM
Hirsch IB, et al. Diabetes Technol Ther. 2008;10(4):

35. Example of Patient With Hypoglycemia
Overcorrection of high blood glucose and overtreatment of low blood glucose could be minimized by use of CGM.
Data on file; DexCom.

36. Example of Response to Food
Patient hesitant to give more insulin before eating—until CGM showed her how high her numbers were traveling after eating a meal.
Data on file; DexCom.

37. Bike (56.4)
Swim (1.2)
Run (13.1)
35 yo Female on Sensor Augmented Insulin Pump Therapy
Longhorn 70.3 mile Triathlon – October 25, 2009

38. Use of CGM During Pregnancy Improves A1c Outcomes
Voelmle---Garg: Diabetes, 57, 2008

39. Current Reimbursement Environment With CGM
A number of national and local payers have issued a positive coverage decision for the personal use of continuous glucose sensors
Other decisions remain on a case-by-case basis for some of the national payers; cash-pay is also an option
If patients purchase up-front, claims can be submitted by the patient to the insurance carrier for review and authorization
Can use Flexible Spending Accounts for purchase of a CGM device

40. General Reimbursement Criteria for Personal Use of CGM
Some insurance plans require only basic criteria of patients needing to have type 1 diabetes and be over the age of 25 (e.g. Aetna)
Other insurance plans require more specific criteria of either some or all of the below criteria:
Type 1 diabetes
Using either multiple daily injection (MDI) or continuous insulin infusion (CSII)
SMBG ≥4/day
Recurring hypoglycemia
Being seen by an endocrinologist
Not meeting ADA glucose guidelines goal of A1c <7%

41. 2009 CGM Coding Reference 95250 3.56 $128 $106 (APC 0607) $310 95251
Description
RVU1
Medicare2 Physician Fee Schedule
Medicare3 Outpatient Diabetes Center
Private Payer4
95250
Ambulatory CGM of ISF via a subcutaneous sensor for a minimum of 72 hrs; sensor placement, hook-up, calibration of monitor, patient training, removal of sensor, and printout of recording
3.56
$128
$106
(APC 0607)
$310
95251
Ambulatory CGM of ISF via a subcutaneous sensor for a minimum of 72 hrs; interpretation and report. Do not report more than once per month
1.10
$40
Paid under physician fee schedule
$54
Evaluation and Management (E/M) Codes
Established Patient Visit
$37-$125
$23-$98
$62-$187
3 CMS Federal Register (November 2008). Fee schedules for E/M codes are MD payment for services provided in a hospital outpatient facility.
4 PMIC Medical Fees in the US Numbers provided are 50% of the Usual and Customary charges. Note that these are charges and not actual reimbursed amounts.
1 CMS Federal Register (November 2008)
2 CMS Federal Register (November 2008) Medicare fee schedule for services in MD office. The fee schedule is not geographically adjusted.

42. What Pattern do you see? Elevated Fasting readings
Overcorrection after meals
Normal fasting glucose but meal related excursions leading to elevated bedtime readings which correct overnight

43. CGM – Type 2 DM What Pattern do you see?

44. T2DM on Pre Mix Insulin BID What pattern do you see?
Controlled but with frequent hypoglycemia
Uncontrolled with fasting hyperglycemia
Uncontrolled with both elevated fasting and postprandial excursions
Normal pattern
Premix insulin: uncontrolled with significant postprandial excursions. Eats 2 meals a day. Anxious about nocturnal hypos and therefore allows BG to run high overnight 44

45. T1DM on Pump Why are fasting glucoses high?
Patient is eating at bedtime
Nocturnal hypoglycemia with rebound high fasting glucose
Dawn phenomenon
fasting
Dawn phenomenon
Increase basal here at 12:00 a.m.

46. Continuous Glucose Monitoring Summary
Tracking and trending information/pattern management
Immediate feedback on how changes in diet, exercise, insulin affect glucose levels
Event Markers can aid in this assessment
Reduction in hypoglycemia/hyperglycemia1,2
Help patients understand A1c by becoming aware of importance of assessing glycemic variability
Increase time in target range1,2
Help patients assess magnitude of glucose excursions1,2
1. Garg S, et al. Diabetes Care. 2006;29(1):44-50.
2. Garg S, Jovanovic L. Diabetes Care. 2006;29(12):

47. Conclusions Current Treatment Targets for Glycemia
Need to be individualized
Be aggressive early in the course of the disease
Treat other comorbidities
Use caution with complicated patients
Avoid hypoglycemia